chore(#15): adopt MULTIMODAL_TEXT_WEIGHT=0.65 + close #15, open #80

A/B eval (eval_retrieval.py, 86-query gold-set) showed the 0.5 default was
mis-tuned: the image side was too heavy and dragged precedent_library recall
0.971 -> 0.885. Sweep 0.5..0.75 — at 0.65 multimodal beats text-only on every
overall metric AND every corpus (R@5 0.994 vs 0.989, nDCG@5 0.960 vs 0.944,
MRR 0.954 vs 0.936). Dafna approved.

- MULTIMODAL_TEXT_WEIGHT=0.65 set in Coolify (legal-ai, runtime) + redeploy.
- baseline.json updated to the 0.65 config (future regression reference).
- #15 done (premise was stale — multimodal already default on 110 docs; the
  win was tuning the weight, not the backfill).
- #80 opened: the costly 140-doc legacy backfill is deferred until a targeted
  image-answer gold-set proves the table/image value prop (untested here).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

data/eval/baseline.json

@@ -2,50 +2,50 @@
   "gold_size": 86,
   "retrieval_config": {
     "MULTIMODAL_ENABLED": true,
-    "VOYAGE_RERANK_ENABLED": true,
+    "VOYAGE_RERANK_ENABLED": false,
     "VOYAGE_MODEL": "voyage-3",
-    "MULTIMODAL_TEXT_WEIGHT": 0.5,
+    "MULTIMODAL_TEXT_WEIGHT": 0.65,
     "MULTIMODAL_RRF_K": 60,
     "BM25_HYBRID_ENABLED": true
   },
   "overall": {
-    "P@5": 0.214,
-    "R@5": 0.899,
-    "nDCG@5": 0.8311,
-    "P@10": 0.1163,
-    "R@10": 0.9649,
-    "nDCG@10": 0.8554,
-    "MRR": 0.8482
+    "P@5": 0.2465,
+    "R@5": 0.9938,
+    "nDCG@5": 0.9597,
+    "P@10": 0.1244,
+    "R@10": 0.9961,
+    "nDCG@10": 0.9611,
+    "MRR": 0.9535
   },
   "by_corpus": {
     "internal_decisions": {
-      "P@5": 0.1963,
-      "R@5": 0.963,
-      "nDCG@5": 0.887,
+      "P@5": 0.2037,
+      "R@5": 1.0,
+      "nDCG@5": 0.978,
       "P@10": 0.1019,
       "R@10": 1.0,
-      "nDCG@10": 0.8994,
-      "MRR": 0.8713
+      "nDCG@10": 0.978,
+      "MRR": 0.9722
     },
     "precedent_library": {
-      "P@5": 0.2438,
-      "R@5": 0.7911,
-      "nDCG@5": 0.7367,
-      "P@10": 0.1406,
-      "R@10": 0.9057,
-      "nDCG@10": 0.7813,
-      "MRR": 0.8092
+      "P@5": 0.3188,
+      "R@5": 0.9833,
+      "nDCG@5": 0.9288,
+      "P@10": 0.1625,
+      "R@10": 0.9896,
+      "nDCG@10": 0.9326,
+      "MRR": 0.9219
     }
   },
   "by_practice_area": {
     "betterment_levy": {
-      "P@5": 0.1897,
-      "R@5": 0.9231,
-      "nDCG@5": 0.8595,
-      "P@10": 0.1,
-      "R@10": 0.9744,
-      "nDCG@10": 0.8766,
-      "MRR": 0.8437
+      "P@5": 0.2051,
+      "R@5": 1.0,
+      "nDCG@5": 0.9621,
+      "P@10": 0.1026,
+      "R@10": 1.0,
+      "nDCG@10": 0.9621,
+      "MRR": 0.9487
     },
     "compensation_197": {
       "P@5": 0.2,
@@ -57,14 +57,14 @@
       "MRR": 1.0
     },
     "rishuy_uvniya": {
-      "P@5": 0.2,
-      "R@5": 0.9706,
-      "nDCG@5": 0.861,
+      "P@5": 0.2059,
+      "R@5": 1.0,
+      "nDCG@5": 0.9976,
       "P@10": 0.1029,
       "R@10": 1.0,
-      "nDCG@10": 0.8708,
-      "MRR": 0.8346
+      "nDCG@10": 0.9976,
+      "MRR": 1.0
     }
   },
-  "generated_at": "20260531T155717Z"
+  "generated_at": "20260603T084350Z"
 }